A computer simulation is a useful step during the design of an electronic circuit to test the various features before a physical embodiment is is built. The circuit may be mathematically modeled in the computer simulator whereby the design parameters may be verified or manipulated to work out the inevitable problems associated with different embodiments before proceeding with the cost and effort of building an actual model. In the case of an artificial neural network, a computer simulation also provides an avenue for graphically displaying the structure of the neural network, that is the synapses, summing junctions, nonlinear sigmoid functions and detailed interconnection thereof, for aiding the circuit designer in understanding the overall operation. The synapses may be shown as circles or ovals connected with lines to the summing junction and sigmoid function.
A neural network may contain hundreds or even thousands of interconnected neurons for providing a single useful function. For such neural networks, conventional display techniques often prohibit the user from displaying the composite network on a single display screen in a meaningful manner in that the large number of synapses, summing junctions and nonlinear sigmoid functions and the maze of connecting lines either cannot physically be contained on the display screen in a readable form, or becomes too confusing for the designer to follow. There are just too many circles and lines leading in many directions to provide a meaningful summary and understanding of its operation. Thus, computer simulators typically restrict the field of display to only a small portion of the neural network for providing at least some useful information. Unfortunately, it is often difficult to grasp the full flavor and operation of the neural network by viewing only a small portion thereof. It would be desirable to simplify the representation of the neural network and avoid the overwhelming detail of the components normally associated therewith.
Hence, there is need for an improved method of graphically displaying large portions if not an entire representation of an artificial neural network in a simplified yet meaningful manner on a computer display terminal without the unnecessary and cumbersome detail of conventional neural network symbolism.